Search results

The purpose of this study is to numerically model the rigid pavement resting on Pasternak soil and to examine its various response parameters and stress resultants like deflection, rotation, bending moment and shear force when subjected to aircraft loading.

The study is carried out using a one-dimensional (1D) beam element based on the finite element method (FEM). Each node in this element has three rotational and three translational degrees of freedom (DOF). MATLAB programming is used to perform the static analysis of rigid pavement.

Response parameters and stress resultants of the rigid pavement were determined. The FEM used in this work is validated by two closed-form numerical examples, which are in great accord with previous research findings with a maximum divergence of 4.64%, therefore verifying the finite element approach used in the current study. Additionally, various parametric studies have been carried out to study the variations in response parameters and stress resultants.

The investigation at hand focuses exclusively on the static analysis of the pavement. The study constraints pertaining to the preliminary design phase of rigid pavements are such that a comprehensive three-dimensional finite element analysis is deemed unnecessary.

As limited previous research had performed the static analysis of rigid pavement on Pasternak foundation with 6 DOF. Furthermore, no prior study has done seven separate parametric investigations on the static analysis of rigid pavement.

The purpose of this study is to numerically model the rigid pavement resting on two-parameter soil and to examine its modal parameters.

This study is carried out using a one-dimensional beam element with three rotational and three translational degrees of freedom based on the finite element method. MATLAB programming is used to perform the free vibration analysis of the rigid pavement.

Cyclic frequency and their corresponding mode shapes were determined. It has been investigated how cyclic frequency changes as a result of variations in the thickness, span length of pavement, shear modulus, modulus of subgrade, different boundary conditions and element discretization. Thickness of the pavement and span length has greater effect on the cyclic frequency. Maximum increase of 29.7% is found on increasing the thickness, whereas the cyclic frequency decreases by 63.49% on increasing span length of pavement.

The pavement's free vibration is the sole subject of the current investigation. This study limits for the preliminary design phase of rigid pavements, where a complete three-dimensional finite element analysis is unnecessary. The current approach can be extended to future research using a different method, such as finite element grilling technique, mesh-free technique on reinforced concrete pavements or jointed concrete pavements.

The finite element approach adopted in this paper involves six degrees of freedom for each node. Furthermore, to the best of the authors’ knowledge, no prior study has done seven separate parametric investigations on the modal analysis of rigid pavement resting on two-parameter soil.

The fundamental period of the structure plays an important role in the seismic analysis. This study aims to analyze the modal response of dam, the two-dimensional (2D) FEM model is developed by using ANSYS 2022 R1 software.

To examine the optimized mesh size to achieve grid independence, the variable element size has been considered, and its optimal value is calculated using the technique of response surface optimization. Further, the effect of damping ratios of 5%, 8% and 10% is also considered for the free vibration analysis of the dam structure.

The results show that the natural frequencies of the dam decrease with a reduction in stiffness of the whole structure. Further, the effect of pre-stress conditions is analyzed and the study has proved that the natural frequency increases after considering the pre-stress as initial condition during modal analysis. Further, it is found that the damping has a substantial effect on frequency for higher modes of vibrations.

The study only focused on modal analysis of the gravity dam, and this study’s results can be used further to evaluate the dynamic behavior of the dam including hydrodynamic conditions.

The finite element tool is used to evaluate the modal response of gravity dam incorporating pre-stress and damping ratio along with soil–structure interaction. Moreover, to the best of the authors’ knowledge, no earlier study has been conducted to evaluate the effect of damping and pre-stress conditions on the stability and natural frequency of the system.

Construction waste reduction (CWR) plays a vital role in achieving sustainability in construction. A good CWR practice can result in optimizing material usage, conserving natural resources, limiting environmental pollution, protecting the environment and enhancing human health. In this regard, the purpose of the current study is to identify the most relevant organizational policies that aid in waste reduction and concurrently explores the congruent measures to be adopted during the construction process in the Indian high-rise building sector.

The research findings were obtained through a mixed- method approach. Content analysis was used to identify waste reduction measures (variables) targeting on the two domains of construction – “waste-efficient execution” and “waste – mitigating organizational policies.” Furthermore, the authors explored and documented the key measures from the identified waste reduction measures using the constraint value of the relative importance index. As the next step, the study listed the theoretical hypothesis based on expert interviews and tested the theory through confirmatory factor analysis.

The results revealed that “waste sensitive construction techniques and strategies” as the most significant category under the domain “Execution” with a path coefficient of 0.85. Concurrently, the study has also determined that “control procedures for budget, quality and resources” as the most effective organizational approach in reducing construction waste in the Indian building industry, with a path coefficient of 0.83.

The current research is context-sensitive to the Indian construction sector. It presents the stakeholder’s perspective on construction waste reduction and the relevant measures to be implemented to reduce construction waste in high-rise building projects in India. It can also act as a concordance for decision-makers to further focus on CWR management and aid in formulating policies suitable for the Indian context.

The issue of evaluating the dynamic characteristics of a bridge due to the presence of rapidly moving vehicles has considerable importance. This study aims to conduct a comprehensive study on the variables that influence the dynamic behavior of a thin-walled box-girder bridge exposed to high-speed train loads using regression analysis.

The high-speed train is mathematically represented by a system with 38 degrees of freedom (DOF), while the sub-track system uses China’s Railway Track System slab track. The numerical modeling of the bridge is accomplished using computationally efficient finite elements that represent thin-walled box-beams. The rail’s imperfections are also accounted for, and they are represented using a power spectral density function. The dynamic response of the bridge is calculated using the Newmark-beta technique, considering several DOFs and stress resultants.

A thorough parametric analysis of the factors affecting the dynamic response of the bridge is conducted and a regression model has been proposed. The regression equation yields an excellent fit for shear force, distortional moment and distortional bimoment, with an R² value near 1. It has also been observed that the range of the coefficient R² in case of bending moment, torsion, torsional bimoment and vertical deflection typically falls between 0.82 and 0.9. R² value near to 1 indicates that it is quite accurate in forecasting the dynamic influence of high-speed trains on the bridge’s response.

The originality of this research lies in pioneering the regression modeling of dynamic responses in thin-walled box-girder bridges and uniquely modeling high-speed trains with 38 DOF, which has not been previously explored in existing studies.

Introduction: The pandemic era has given rise to emerging VUCA factors, characterised by volatility, uncertainty, complexity, and ambiguity. Navigating the impact of these challenges is essential for adapting and thriving in a post-pandemic world; therefore, it is important to identify VUCA factors.

Purpose: The purpose of this study is to identify and analyse the VUCA factors that emerged during the COVID-19 pandemic, focusing on sectors such as hospitality, tourism, education, construction, manufacturing, Information Technology, healthcare, and automobiles.

Need for the Study: Analysing emerging VUCA factors is crucial for businesses to prepare for unforeseen events. While VUCA factors were previously studied during significant events like the Greater Recession, BREXIT, and demonetisation, the pandemic has presented unprecedented challenges, making the identification of emerging VUCA components crucial.

Methodology: The methodology involves reviewing articles and research papers to understand the pandemic’s impact on various sectors. The findings provide insights into prominent VUCA factors and their implications for businesses, contributing to existing knowledge.

Findings: This research uncovers the challenges organisations encountered in the pandemic’s VUCA environment, offering insights into uncertainties and strategies for survival. It highlights the importance of adaptability, resilience, and innovation in overcoming VUCA’s negative impacts and establishing a new business paradigm.

Practical Implications: This chapter is essential in providing valuable insights for organisations, policymakers, and businesses on crisis preparedness, emphasising the significance of agility, robust contingency planning, and sector-specific considerations. Reviewing operations and implementing backup plans, businesses can develop effective strategies for long-term resilience and success in the face of unforeseen disruptions.

The tourism industry is undergoing a metamorphosis as an outcome of the integration of new technologies, which has an impact on products, business experiences, ecosystems and tourism complexes. As a result, to adjust to these changes, the sector needs to develop new business alliances, models and skill sets. Emerging technologies such as virtual reality (VR), augmented reality (AR), artificial intelligence (AI), and data analytics are set to bring in a new chapter in the history of travel experiences. Deepening global linkages, optimising operating efficiency, and transforming visitor experiences are all being brought about by these advancements. The report also evaluates the wider effects of this digital revolution, such as the levelling of access to travel information, the introduction of fresh business strategies and the crucial role of cyber security. With practical advice drawn from empirical research, real-world case studies and industry expert interviews, this study prepares businesses and travel destinations for success in the digital age. ‘From Pixels to Paradise’ is an indispensable tool for all those involved in the travel and tourism sector, helping them navigate the digital environment and take advantage of the opportunities brought about by the convergence of travel and technology. This study tries to map out a route towards a more sustainable, engaging and technologically improved tourism experience against the backdrop of significant industry changes.

This study aims to investigate the extent and pattern of the influence of one of the most important decision-making tools in the context of social commerce. This study demonstrates how much customer testimonials (including verified purchases and ordinary users) can influence the sales rank of experience and search goods.

The data were collected by text mining and performing a content analysis on the XML documents of Web pages and processing them. For search goods, 22,311 opinions were recorded regarding 95 mobile phones. Additionally, for experience goods, 67,817 opinions were recorded regarding 162 books in the Amazon online store. The data were analyzed by functional regression method in longitudinal data analysis.

In terms of importance, the opinions and recommendations of verified purchases had a 60% greater impact on the sales rank of experience goods than the opinions and recommendations of ordinary users. In search goods, the opinions of ordinary users had a greater impact than the opinions of verified purchases. The historical effect of the opinions of ordinary users at the end of the review period on sales rank was evident, while the historical effect of the verified purchase viewpoints during the review period had a nonlinear curve. The results showed that it was necessary to increase the volume of comments to increase their reliability in experience goods.

Measuring the effect of customer testimonials helps the managers of retail websites design algorithms and online suggestion systems, thereby improving the sales of their products by providing information desired by customers.

Individuals can be a source of information and influence the buying decision process of others by sharing their experiences. This issue helps reduce the purchase risk and explains the importance of interaction and sharing the customer’s experience.

Analyzing the impact of customer testimonials by separating verified purchases and ordinary users is one of the advantages of this study. The quantitative estimation of the impact of recommendations and the provision of a model of their historical effect is one of the approaches not addressed in similar studies.